APPLIED STAT.IN BUS.+ECONOMICS
6th Edition
ISBN: 9781259957598
Author: DOANE
Publisher: RENT MCG
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Question
Chapter 12.11, Problem 44SE
a.
To determine
Find the predicted probability of a 401(k) plan for an employee whose salary is $3,000 using the fitted equation.
b.
To determine
Find the predicted probability of a 401(k) plan for an employee whose salary is $5,000 using the fitted equation.
c.
To determine
Find the predicted probability of a 401(k) plan for an employee whose salary is $8,000 using the fitted equation.
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Check out a sample textbook solutionChapter 12 Solutions
APPLIED STAT.IN BUS.+ECONOMICS
Ch. 12.1 - For each sample, do a test for zero correlation....Ch. 12.1 - Instructions for Exercises 12.2 and 12.3: (a) Make...Ch. 12.1 - Prob. 3SECh. 12.1 - Prob. 4SECh. 12.1 - Instructions for exercises 12.412.6: (a) Make a...Ch. 12.1 - Prob. 6SECh. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.2 - Prob. 9SECh. 12.2 - (a) Interpret the slope of the fitted regression...
Ch. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.3 - Prob. 12SECh. 12.3 - Prob. 13SECh. 12.3 - The regression equation Credits = 15.4 .07 Work...Ch. 12.3 - Below are fitted regressions for Y = asking price...Ch. 12.3 - Refer back to the regression equation in exercise...Ch. 12.3 - Refer back to the regression equation in exercise...Ch. 12.4 - Instructions for exercises 12.18 and 12.19: (a)...Ch. 12.4 - Instructions for exercises 12.18 and 12.19: (a)...Ch. 12.4 - Instructions for exercises 12.2012.22: (a) Use...Ch. 12.4 - Instructions for exercises 12.2012.22: (a) Use...Ch. 12.4 - Instructions for exercises 12.2012.22: (a) Use...Ch. 12.5 - Instructions for exercises 12.23 and 12.24: (a)...Ch. 12.5 - Instructions for exercises 12.23 and 12.24: (a)...Ch. 12.5 - A regression was performed using data on 32 NFL...Ch. 12.5 - A regression was performed using data on 16...Ch. 12.6 - Below is a regression using X = home price (000),...Ch. 12.6 - Below is a regression using X = average price, Y =...Ch. 12.6 - Instructions for exercises 12.2912.31: (a) Use...Ch. 12.6 - Instructions for exercises 12.2912.31: (a) Use...Ch. 12.6 - Instructions for exercises 12.2912.31: (a) Use...Ch. 12.7 - Refer to the Weekly Earnings data set below. (a)...Ch. 12.7 - Prob. 33SECh. 12.8 - Prob. 34SECh. 12.8 - Prob. 35SECh. 12.9 - Calculate the standardized residual ei and...Ch. 12.9 - Prob. 37SECh. 12.9 - An estimated regression for a random sample of...Ch. 12.9 - An estimated regression for a random sample of...Ch. 12.9 - Prob. 40SECh. 12.9 - Prob. 41SECh. 12.9 - Prob. 42SECh. 12.9 - Prob. 43SECh. 12.11 - Prob. 44SECh. 12.11 - Prob. 45SECh. 12 - (a) How does correlation analysis differ from...Ch. 12 - (a) What is a simple regression model? (b) State...Ch. 12 - (a) Explain how you fit a regression to an Excel...Ch. 12 - (a) Explain the logic of the ordinary least...Ch. 12 - (a) Why cant we use the sum of the residuals to...Ch. 12 - Prob. 6CRCh. 12 - Prob. 7CRCh. 12 - Prob. 8CRCh. 12 - Prob. 9CRCh. 12 - Prob. 10CRCh. 12 - Prob. 11CRCh. 12 - Prob. 12CRCh. 12 - (a) What is heteroscedasticity? Identify its two...Ch. 12 - (a) What is autocorrelation? Identify two main...Ch. 12 - Prob. 15CRCh. 12 - Prob. 16CRCh. 12 - (a) What is a log transform? (b) What are its...Ch. 12 - (a) When is logistic regression needed? (b) Why...Ch. 12 - Prob. 46CECh. 12 - Prob. 47CECh. 12 - Prob. 48CECh. 12 - Instructions: Choose one or more of the data sets...Ch. 12 - Prob. 50CECh. 12 - Prob. 51CECh. 12 - Prob. 52CECh. 12 - Prob. 53CECh. 12 - Instructions: Choose one or more of the data sets...Ch. 12 - Instructions: Choose one or more of the data sets...Ch. 12 - Instructions: Choose one or more of the data sets...Ch. 12 - Prob. 57CECh. 12 - Prob. 58CECh. 12 - Prob. 59CECh. 12 - Prob. 60CECh. 12 - Prob. 61CECh. 12 - Prob. 62CECh. 12 - Prob. 63CECh. 12 - Prob. 64CECh. 12 - Prob. 65CECh. 12 - In the following regression, X = weekly pay, Y =...Ch. 12 - Prob. 67CECh. 12 - In the following regression, X = total assets (...Ch. 12 - Prob. 69CECh. 12 - Below are percentages for annual sales growth and...Ch. 12 - Prob. 71CECh. 12 - Prob. 72CECh. 12 - Prob. 73CECh. 12 - Simple regression was employed to establish the...Ch. 12 - Prob. 75CECh. 12 - Prob. 76CECh. 12 - Prob. 77CECh. 12 - Below are revenue and profit (both in billions)...Ch. 12 - Below are fitted regressions based on used vehicle...Ch. 12 - Below are results of a regression of Y = average...Ch. 12 - Prob. 81CE
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- Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?arrow_forwardTable 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?arrow_forwardWhat is the y -intercept on the graph of the logistic model given in the previous exercise?arrow_forward
- Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardDoes a linear, exponential, or logarithmic model best fit the data in Table 2? Find the model.arrow_forwardWhat might a scatterplot of data points look like if it were best described by a logarithmic model?arrow_forward
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